Cross-Validated Kernel Ensemble

Implementation of Cross-Validated Kernel Ensemble (CVEK), a flexible modeling framework for robust nonlinear regression and hypothesis testing based on ensemble learning with kernel-ridge estimators (Jeremiah et al. (2017) and Wenying et al. (2018) ). It allows user to conduct nonlinear regression with minimal assumption on the function form by aggregating nonlinear models generated from a diverse collection of kernel families. It also provides utilities to test for the estimated nonlinear effect under this ensemble estimator, using either the asymptotic or the bootstrap version of a generalized score test.


Reference manual

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0.1-2 by Wenying Deng, a year ago

Browse source code at

Authors: Wenying Deng [aut, cre] , Jeremiah Zhe Liu [ctb]

Documentation:   PDF Manual  

GPL-2 license

Depends on MASS, limSolve

Suggests testthat, knitr, rmarkdown, ggplot2, ggrepel

See at CRAN